Test Driven Development (TDD), and Refactoring Legacy Code Using Java

Duration: 4 Days (Face-to-Face or Remote-Live), or 28 hours of coursework with personal facilitation over a four week span (On-Demand)

US Price: $2095 (Face-to-Face or Remote-Live), or $1495 (On-Demand)

Delivery Options: Attend face-to-face in the classroom, remote-live or via on-demand training

Registration: Click here to view upcoming schedules and register for face-to-face sessions, click here to register for live remote attendance sessions, or click here to register for on-demand training with a start date that is convenient for you.

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Description

This Test Driven Development (TDD) training course provides students with hands on experience learning TDD methodology in the context of Java software development. Students build unit tests using mocks, fakes, stubs and drivers, and address issues working with databases and other systems. Students learn how to create tests that assure that code will meet and exceed requirements. The course shows how regression testing assures that code that receives “test coverage” will not break existing systems, because tests are passed before code is checked in.

Students will spend time working with the issues involved in refactoring legacy code, safely cutting into an already deployed system. Students will work on looking for, or creating “seams” to more safely improve code or add features, and work on identifying “code smells” that need attention in a productive system. Finally, students will explore dependency issues as well as techniques to better understand and improve complex systems.

Comprehensive labs using Java and JUnit provide facilitated hands on practice throughout the course to develop competence and confidence with the new skills being learned.

Prerequisites

Java programming experience and an understanding of object-oriented design principles. The Java Programming course or equivalent knowledge provides a solid foundation.

Course Overview

Why TDD? Think Twice, Write Production Code Once Utilizing a Safety Net of Automated Testing Agile Development Concepts Eliminating Bugs Early Smoothing Out Production Rollouts Writing Code Faster via Testing Reducing Technical Debt Practicing Emergent Design Making Changes More Safe The Importance of Regression Testing	Basic Unit Testing JUnit Testing with JUnit Adding Complexity to Initial Simple Tests Making Tests Easy to Run The TDD Pattern: Red, Green Refactor Using Methods of the Assert Class Boundary Testing Unit Test Limitations
Comprehensive Unit Testing Concepts Using Declarative-Style Attributes Using Hamcrest Matchers for More Complex Scenarios Using Test Categories Exception Handling in Tests JUnit Test Initialization and Clean Up Methods Writing Clean and Dirty Tests Testing with Collections, Generics and Arrays Negative Testing	Mocks, Fakes, Stubs and Drivers TDD Development Patterns Naming Conventions for Better Code Using Mock Objects Using Fakes Using Stubs Test Doubles Manual Mocking Mocking with a Mock Framework Self-Shunt Pattern
Database Unit Testing Mocking the Data Layer Identifying what Should Be Tested in Databases Stored Procedure Tests Schema Testing Using NDbUnit to Set Up the DB Test Environment	Refactoring Basics Refactoring Existing Code Restructuring Extracting Methods Removing Duplication Reducing Coupling Division of Responsibilities Improving Clarity and Maintainability Test First - then Refactor More Complex Refactoring Considerations
Patterns and Anti-Patterns in TDD The SOLID Principles Factory Methods Coding to Interface References Checking Parameters for Validity Test Open/Closed Principle: Open to Extension, Closed to Change Breaking Out Method/Object Extract and Override Call Extract and Override Factory Method Singleton Pattern Decorator Pattern Facade Pattern State Pattern MVP, MVC and MVVM Patterns Finding and Removing Code Smells/Antipatterns	Refactoring Legacy Code Reducing Risk of Change Eliminating Dependencies Characterization Tests as a Safety Net Introducing Abstractions to Break Dependencies Analyzing Legacy Code Identifying Pinch Points with Effect Analysis Identifying Seams for Expansion and Testing Listing Markup Minimizing Risk of Adding New Behavior Sprout Method Sprout Class Wrap Method Wrap Class Dealing with Code that's Difficult to Test Globals and Singletons in Tests Inaccessible Methods and Fields Using Smells to Identify What to Refactor Dealing with Monster Methods Dealing with Excessively Complex, Large Classes Identifying and Eliminating Duplication Other Smells Dealing with Large Legacy Systems Preserving Signatures
Code Coverage White Box vs Black Box Testing Planning to Increase Code Coverage Over Time Goal 80% or More Test Coverage Statement Coverage Condition Coverage Path Coverage	Risks Changing Legacy/Production Systems Refactoring Coupling and Cohesion Issues Taking Small Tested Steps